Huygens Cluster Analyzer

Obtain reliable analysis fast and easy.

- Available as an add-on for all Huygens LOCALIZER smlm packages.-

Anyone interested in cluster-related research questions recieves an answer within minutes using Huygens Cluster Analyzer. The build-in Tutorial guides you as a beginner through the first steps of its use. Available FOCAL and DBSCAN algoritms for clustering localizations are thouroughly described, and each parameter is well-explained via a tool tip.
When adjusting the FOCAL and DBSCAN parameters, clusters are 3D-rendered at the highest possible quality and counted on-the-fly. By simply clicking the button "Analyze all clusters" results are presented in a table within a split second. Parameters for the table can be selected as presets and include localization density, volume, width, length, distances, and colocalization. They are highlighted in the table when selecting the corresponding cluster within the 3D scene - and vice versa. Various filters can be applied to focus on specific clusters, and the final analysis results can be exported for use in spreadsheets and Matlab.

Animation description
Clusters are 3D rendered at the best possible quality with Huygens ray-tracing, and analyzed at highest detail within a split second.

Cluster Analyzer General Screenshot Id Labels

Main features

The Cluster Analyzer features:
  • FOCAL or DBSCAN algorithms to cluster the localizations in 2D/3D.
  • In-tool tutorial to get started quickly and to familiarize yourself with the main features.
  • Easy-to-use Estimator tool for determining the optimal FOCAL parameters.
  • High quality 2D/3D iso-surface rendering of clusters using ray tracing.
  • On-the-fly counting of the clusters.
  • Direct link between rendered scene and table with cluster statistics: the selected cluster is highlight in both.
  • Analysis presets available for geometry, colocalization analysis, and first neighbor
  • Geometry measurements include localization density, volume, surface, width, length, and more...
  • Object-based Colocalization Analysis
  • Extensive filtering tools to refine the cluster analysis.
  • Save option to export cluster statistics to spreadsheets (.txt or .csv) or Matlab (.m).
  • MIP rendering to use of a specified channel as a reference for determining optimal cluster parameters.
  • Clear tool tips with explanations about each parameter.
  • Optimal performance with CPU and GPU support.